Conference item
Estimation of HRV and SpO2 from wrist-worn commercial sensors for clinical settings
- Abstract:
- We describe an evaluation of photoplethysmography (PPG) signals with two wavelengths channels (infrared and red) using a wrist-worn sensor for the estimation of heart rate variability (HRV) and oxygen saturation (SpO2). Five healthy subjects were equipped with a commercial wrist-worn pulse oximeter (Wavelet Health, USA) on the right hand, and both a commercial smart watch for fitness use (Huawei Watch, Series 2) and a clinically-validated transmission-mode pulse oximeter (Creative Medical PC-68B) on their left hand as a reference. Synchronised PPG signals from the Wavelet Health, the Huawei watch, and the PC-68B were recorded for approximately 10 minutes. Subjects were asked to leave the left hand in a resting state, while moving the right hand with two types of movement (periodic and random). A method is proposed to incorporate coupling information between the two wavelengths of PPGs based on the bivariate empirical mode decomposition algorithm. Our method is shown to improve the quality of red PPG allowing improved estimation of SpO2. A comparison of average heart rate (HR), HRV, and SpO2 from all devices is provided.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 1.6MB, Terms of use)
-
- Publisher copy:
- 10.1109/BSN.2018.8329679
Authors
- Publisher:
- Institute of Electrical and Electronics Engineers
- Host title:
- Proceedings of the 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN 2018)
- Pages:
- 144-147
- Publication date:
- 2018-04-05
- Event title:
- 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN)
- Event location:
- Las Vegas, NV, USA
- Event website:
- https://www.aconf.org/conf_114656.html
- Event start date:
- 2018-03-04
- Event end date:
- 2018-03-07
- DOI:
- EISSN:
-
2376-8886
- EISBN:
- 9781538611098
- ISBN:
- 9781538611104
- Language:
-
English
- Keywords:
- Pubs id:
-
889391
- Local pid:
-
pubs:889391
- Deposit date:
-
2021-04-12
- ARK identifier:
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2018
- Rights statement:
- © IEEE 2018.
- Notes:
- This paper was presented at the 2018 IEEE 15th International Conference on Wearable and Implantable Body Sensor Networks (BSN 2018). This the accepted manuscript version of the article. The final version is available from IEEE at: https://doi.org/10.1109/BSN.2018.8329679
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